Overview

Dataset statistics

Number of variables22
Number of observations8399
Missing cells63
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.4 MiB
Average record size in memory172.0 B

Variable types

Numeric9
DateTime2
Categorical9
Text2

Alerts

Row ID is uniformly distributedUniform
Row ID has unique valuesUnique
Discount has 756 (9.0%) zerosZeros

Reproduction

Analysis started2024-07-09 11:51:30.618550
Analysis finished2024-07-09 11:51:50.118106
Duration19.5 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Row ID
Real number (ℝ)

UNIFORM  UNIQUE 

Distinct8399
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4200
Minimum1
Maximum8399
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:50.362487image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile420.9
Q12100.5
median4200
Q36299.5
95-th percentile7979.1
Maximum8399
Range8398
Interquartile range (IQR)4199

Descriptive statistics

Standard deviation2424.7268
Coefficient of variation (CV)0.5773159
Kurtosis-1.2
Mean4200
Median Absolute Deviation (MAD)2100
Skewness0
Sum35275800
Variance5879300
MonotonicityNot monotonic
2024-07-09T17:21:50.648015image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1317 1
 
< 0.1%
1315 1
 
< 0.1%
1199 1
 
< 0.1%
1155 1
 
< 0.1%
1109 1
 
< 0.1%
1007 1
 
< 0.1%
867 1
 
< 0.1%
866 1
 
< 0.1%
698 1
 
< 0.1%
Other values (8389) 8389
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
8399 1
< 0.1%
8398 1
< 0.1%
8397 1
< 0.1%
8396 1
< 0.1%
8395 1
< 0.1%
8394 1
< 0.1%
8393 1
< 0.1%
8392 1
< 0.1%
8391 1
< 0.1%
8390 1
< 0.1%

Order ID
Real number (ℝ)

Distinct5496
Distinct (%)65.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29965.18
Minimum3
Maximum59973
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:50.925797image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile2818
Q115011.5
median29857
Q344596
95-th percentile57061
Maximum59973
Range59970
Interquartile range (IQR)29584.5

Descriptive statistics

Standard deviation17260.883
Coefficient of variation (CV)0.57603137
Kurtosis-1.1783167
Mean29965.18
Median Absolute Deviation (MAD)14778
Skewness0.0038108922
Sum2.5167754 × 108
Variance2.979381 × 108
MonotonicityNot monotonic
2024-07-09T17:21:51.212142image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24132 6
 
0.1%
43745 6
 
0.1%
33797 5
 
0.1%
12261 5
 
0.1%
58784 5
 
0.1%
42528 5
 
0.1%
12067 5
 
0.1%
13540 5
 
0.1%
58470 5
 
0.1%
57253 5
 
0.1%
Other values (5486) 8347
99.4%
ValueCountFrequency (%)
3 1
 
< 0.1%
6 1
 
< 0.1%
32 4
< 0.1%
35 2
< 0.1%
36 1
 
< 0.1%
65 1
 
< 0.1%
66 1
 
< 0.1%
69 2
< 0.1%
70 2
< 0.1%
96 1
 
< 0.1%
ValueCountFrequency (%)
59973 2
< 0.1%
59971 3
< 0.1%
59969 2
< 0.1%
59943 1
 
< 0.1%
59942 1
 
< 0.1%
59939 1
 
< 0.1%
59937 1
 
< 0.1%
59911 1
 
< 0.1%
59909 2
< 0.1%
59906 1
 
< 0.1%
Distinct1418
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Minimum2009-01-01 00:00:00
Maximum2012-12-30 00:00:00
2024-07-09T17:21:51.525403image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:51.854316image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Order Priority
Categorical

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
High
1768 
Low
1720 
Not Specified
1672 
Medium
1631 
Critical
1608 

Length

Max length13
Median length6
Mean length6.7410406
Min length3

Characters and Unicode

Total characters56618
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLow
2nd rowHigh
3rd rowHigh
4th rowHigh
5th rowNot Specified

Common Values

ValueCountFrequency (%)
High 1768
21.1%
Low 1720
20.5%
Not Specified 1672
19.9%
Medium 1631
19.4%
Critical 1608
19.1%

Length

2024-07-09T17:21:52.140001image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:21:52.417882image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
high 1768
17.6%
low 1720
17.1%
not 1672
16.6%
specified 1672
16.6%
medium 1631
16.2%
critical 1608
16.0%

Most occurring characters

ValueCountFrequency (%)
i 9959
17.6%
e 4975
 
8.8%
o 3392
 
6.0%
d 3303
 
5.8%
t 3280
 
5.8%
c 3280
 
5.8%
H 1768
 
3.1%
g 1768
 
3.1%
h 1768
 
3.1%
L 1720
 
3.0%
Other values (13) 21405
37.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 44875
79.3%
Uppercase Letter 10071
 
17.8%
Space Separator 1672
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 9959
22.2%
e 4975
11.1%
o 3392
 
7.6%
d 3303
 
7.4%
t 3280
 
7.3%
c 3280
 
7.3%
g 1768
 
3.9%
h 1768
 
3.9%
w 1720
 
3.8%
f 1672
 
3.7%
Other values (6) 9758
21.7%
Uppercase Letter
ValueCountFrequency (%)
H 1768
17.6%
L 1720
17.1%
S 1672
16.6%
N 1672
16.6%
M 1631
16.2%
C 1608
16.0%
Space Separator
ValueCountFrequency (%)
1672
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 54946
97.0%
Common 1672
 
3.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 9959
18.1%
e 4975
 
9.1%
o 3392
 
6.2%
d 3303
 
6.0%
t 3280
 
6.0%
c 3280
 
6.0%
H 1768
 
3.2%
g 1768
 
3.2%
h 1768
 
3.2%
L 1720
 
3.1%
Other values (12) 19733
35.9%
Common
ValueCountFrequency (%)
1672
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56618
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 9959
17.6%
e 4975
 
8.8%
o 3392
 
6.0%
d 3303
 
5.8%
t 3280
 
5.8%
c 3280
 
5.8%
H 1768
 
3.1%
g 1768
 
3.1%
h 1768
 
3.1%
L 1720
 
3.0%
Other values (13) 21405
37.8%

Order Quantity
Real number (ℝ)

Distinct50
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.571735
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:52.711715image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q113
median26
Q338
95-th percentile48
Maximum50
Range49
Interquartile range (IQR)25

Descriptive statistics

Standard deviation14.481071
Coefficient of variation (CV)0.56629209
Kurtosis-1.2080203
Mean25.571735
Median Absolute Deviation (MAD)13
Skewness-0.017317782
Sum214777
Variance209.70142
MonotonicityNot monotonic
2024-07-09T17:21:53.005562image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
31 202
 
2.4%
4 196
 
2.3%
39 195
 
2.3%
46 193
 
2.3%
24 192
 
2.3%
23 192
 
2.3%
42 189
 
2.3%
3 189
 
2.3%
43 184
 
2.2%
41 183
 
2.2%
Other values (40) 6484
77.2%
ValueCountFrequency (%)
1 165
2.0%
2 152
1.8%
3 189
2.3%
4 196
2.3%
5 166
2.0%
6 172
2.0%
7 174
2.1%
8 176
2.1%
9 155
1.8%
10 170
2.0%
ValueCountFrequency (%)
50 182
2.2%
49 136
1.6%
48 172
2.0%
47 166
2.0%
46 193
2.3%
45 163
1.9%
44 157
1.9%
43 184
2.2%
42 189
2.3%
41 183
2.2%

Sales
Real number (ℝ)

Distinct8153
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1775.8782
Minimum2.24
Maximum89061.05
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:53.298494image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum2.24
5-th percentile34.178
Q1143.195
median449.42
Q31709.32
95-th percentile7844.335
Maximum89061.05
Range89058.81
Interquartile range (IQR)1566.125

Descriptive statistics

Standard deviation3585.0505
Coefficient of variation (CV)2.018748
Kurtosis60.928376
Mean1775.8782
Median Absolute Deviation (MAD)381.95
Skewness5.3869824
Sum14915601
Variance12852587
MonotonicityNot monotonic
2024-07-09T17:21:53.601228image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
74.02 3
 
< 0.1%
43.29 3
 
< 0.1%
10.48 3
 
< 0.1%
224.58 3
 
< 0.1%
151.19 3
 
< 0.1%
20.19 3
 
< 0.1%
127.56 3
 
< 0.1%
46.94 3
 
< 0.1%
19.36 3
 
< 0.1%
75.19 3
 
< 0.1%
Other values (8143) 8369
99.6%
ValueCountFrequency (%)
2.24 1
< 0.1%
3.2 1
< 0.1%
3.23 1
< 0.1%
3.41 1
< 0.1%
3.42 1
< 0.1%
3.63 1
< 0.1%
3.77 1
< 0.1%
3.85 1
< 0.1%
3.96 1
< 0.1%
4.94 1
< 0.1%
ValueCountFrequency (%)
89061.05 1
< 0.1%
45923.76 1
< 0.1%
41343.21 1
< 0.1%
33367.85 1
< 0.1%
29884.6 1
< 0.1%
29345.27 1
< 0.1%
29186.49 1
< 0.1%
28761.52 1
< 0.1%
28664.52 1
< 0.1%
28389.14 1
< 0.1%

Discount
Real number (ℝ)

ZEROS 

Distinct16
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.049671389
Minimum0
Maximum0.25
Zeros756
Zeros (%)9.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:53.845741image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.02
median0.05
Q30.08
95-th percentile0.1
Maximum0.25
Range0.25
Interquartile range (IQR)0.06

Descriptive statistics

Standard deviation0.03182302
Coefficient of variation (CV)0.64067102
Kurtosis-0.95941106
Mean0.049671389
Median Absolute Deviation (MAD)0.03
Skewness0.073916963
Sum417.19
Variance0.0010127046
MonotonicityNot monotonic
2024-07-09T17:21:54.089302image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0.01 806
9.6%
0.05 786
9.4%
0.03 779
9.3%
0.09 778
9.3%
0.04 770
9.2%
0.08 765
9.1%
0.02 765
9.1%
0 756
9.0%
0.1 745
8.9%
0.06 734
8.7%
Other values (6) 715
8.5%
ValueCountFrequency (%)
0 756
9.0%
0.01 806
9.6%
0.02 765
9.1%
0.03 779
9.3%
0.04 770
9.2%
0.05 786
9.4%
0.06 734
8.7%
0.07 710
8.5%
0.08 765
9.1%
0.09 778
9.3%
ValueCountFrequency (%)
0.25 1
 
< 0.1%
0.21 1
 
< 0.1%
0.17 1
 
< 0.1%
0.16 1
 
< 0.1%
0.11 1
 
< 0.1%
0.1 745
8.9%
0.09 778
9.3%
0.08 765
9.1%
0.07 710
8.5%
0.06 734
8.7%

Ship Mode
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Regular Air
6270 
Delivery Truck
1146 
Express Air
983 

Length

Max length14
Median length11
Mean length11.409334
Min length11

Characters and Unicode

Total characters95827
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRegular Air
2nd rowDelivery Truck
3rd rowRegular Air
4th rowRegular Air
5th rowRegular Air

Common Values

ValueCountFrequency (%)
Regular Air 6270
74.7%
Delivery Truck 1146
 
13.6%
Express Air 983
 
11.7%

Length

2024-07-09T17:21:54.350578image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:21:54.595778image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
air 7253
43.2%
regular 6270
37.3%
delivery 1146
 
6.8%
truck 1146
 
6.8%
express 983
 
5.9%

Most occurring characters

ValueCountFrequency (%)
r 16798
17.5%
e 9545
10.0%
8399
8.8%
i 8399
8.8%
u 7416
7.7%
l 7416
7.7%
A 7253
7.6%
R 6270
 
6.5%
g 6270
 
6.5%
a 6270
 
6.5%
Other values (10) 11791
12.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70630
73.7%
Uppercase Letter 16798
 
17.5%
Space Separator 8399
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 16798
23.8%
e 9545
13.5%
i 8399
11.9%
u 7416
10.5%
l 7416
10.5%
g 6270
 
8.9%
a 6270
 
8.9%
s 1966
 
2.8%
v 1146
 
1.6%
y 1146
 
1.6%
Other values (4) 4258
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
A 7253
43.2%
R 6270
37.3%
T 1146
 
6.8%
D 1146
 
6.8%
E 983
 
5.9%
Space Separator
ValueCountFrequency (%)
8399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 87428
91.2%
Common 8399
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 16798
19.2%
e 9545
10.9%
i 8399
9.6%
u 7416
8.5%
l 7416
8.5%
A 7253
8.3%
R 6270
 
7.2%
g 6270
 
7.2%
a 6270
 
7.2%
s 1966
 
2.2%
Other values (9) 9825
11.2%
Common
ValueCountFrequency (%)
8399
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 95827
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 16798
17.5%
e 9545
10.0%
8399
8.8%
i 8399
8.8%
u 7416
7.7%
l 7416
7.7%
A 7253
7.6%
R 6270
 
6.5%
g 6270
 
6.5%
a 6270
 
6.5%
Other values (10) 11791
12.3%

Profit
Real number (ℝ)

Distinct7986
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean181.18442
Minimum-14140.702
Maximum27220.69
Zeros0
Zeros (%)0.0%
Negative4264
Negative (%)50.8%
Memory size65.7 KiB
2024-07-09T17:21:54.856476image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum-14140.702
5-th percentile-592.43905
Q1-83.315
median-1.5
Q3162.748
95-th percentile1542.309
Maximum27220.69
Range41361.392
Interquartile range (IQR)246.063

Descriptive statistics

Standard deviation1196.6533
Coefficient of variation (CV)6.6046149
Kurtosis67.34971
Mean181.18442
Median Absolute Deviation (MAD)104.3345
Skewness3.6472388
Sum1521768
Variance1431979.2
MonotonicityNot monotonic
2024-07-09T17:21:55.125195image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-969.048366 8
 
0.1%
-433.290143 6
 
0.1%
11.65095 5
 
0.1%
-715.778206 5
 
0.1%
-1331.553366 5
 
0.1%
-528.653125 5
 
0.1%
-505.984479 5
 
0.1%
-66.87 4
 
< 0.1%
-513.79042 4
 
< 0.1%
-22.82 4
 
< 0.1%
Other values (7976) 8348
99.4%
ValueCountFrequency (%)
-14140.7016 1
< 0.1%
-12557.9976 1
< 0.1%
-11984.3979 1
< 0.1%
-11861.46 1
< 0.1%
-11769.17 1
< 0.1%
-11053.6 1
< 0.1%
-10263.6597 1
< 0.1%
-9611.91 1
< 0.1%
-9078.94 1
< 0.1%
-8570.4483 1
< 0.1%
ValueCountFrequency (%)
27220.69 1
< 0.1%
14440.39 1
< 0.1%
13340.26 1
< 0.1%
12748.86 1
< 0.1%
12606.81 1
< 0.1%
11984.395 1
< 0.1%
11630.146 1
< 0.1%
11562.08 1
< 0.1%
11535.282 1
< 0.1%
10951.3065 1
< 0.1%

Unit Price
Real number (ℝ)

Distinct751
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.346259
Minimum0.99
Maximum6783.02
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:55.386646image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.99
5-th percentile2.88
Q16.48
median20.99
Q385.99
95-th percentile320.64
Maximum6783.02
Range6782.03
Interquartile range (IQR)79.51

Descriptive statistics

Standard deviation290.35438
Coefficient of variation (CV)3.2497654
Kurtosis271.16873
Mean89.346259
Median Absolute Deviation (MAD)17.01
Skewness14.127793
Sum750419.23
Variance84305.668
MonotonicityNot monotonic
2024-07-09T17:21:55.721910image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6.48 264
 
3.1%
65.99 192
 
2.3%
4.98 136
 
1.6%
125.99 115
 
1.4%
5.98 102
 
1.2%
2.88 81
 
1.0%
30.98 73
 
0.9%
20.99 73
 
0.9%
35.99 70
 
0.8%
19.98 66
 
0.8%
Other values (741) 7227
86.0%
ValueCountFrequency (%)
0.99 2
 
< 0.1%
1.14 10
 
0.1%
1.26 13
0.2%
1.48 12
0.1%
1.6 5
 
0.1%
1.68 22
0.3%
1.7 8
 
0.1%
1.74 9
 
0.1%
1.76 29
0.3%
1.8 3
 
< 0.1%
ValueCountFrequency (%)
6783.02 7
0.1%
3502.14 6
0.1%
3499.99 7
0.1%
2550.14 7
0.1%
2036.48 6
0.1%
1938.02 8
0.1%
1889.99 3
 
< 0.1%
1637.53 2
 
< 0.1%
1500.97 5
0.1%
1360.14 3
 
< 0.1%

Shipping Cost
Real number (ℝ)

Distinct652
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.838557
Minimum0.49
Maximum164.73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:56.015576image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.49
5-th percentile0.8
Q13.3
median6.07
Q313.99
95-th percentile55.351
Maximum164.73
Range164.24
Interquartile range (IQR)10.69

Descriptive statistics

Standard deviation17.264052
Coefficient of variation (CV)1.3447035
Kurtosis7.7515872
Mean12.838557
Median Absolute Deviation (MAD)3.61
Skewness2.5538008
Sum107831.04
Variance298.04749
MonotonicityNot monotonic
2024-07-09T17:21:56.317329image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19.99 352
 
4.2%
8.99 321
 
3.8%
1.99 247
 
2.9%
0.5 190
 
2.3%
0.99 144
 
1.7%
4 143
 
1.7%
1.49 138
 
1.6%
0.7 138
 
1.6%
24.49 132
 
1.6%
2.99 124
 
1.5%
Other values (642) 6470
77.0%
ValueCountFrequency (%)
0.49 34
 
0.4%
0.5 190
2.3%
0.7 138
1.6%
0.71 22
 
0.3%
0.73 1
 
< 0.1%
0.75 7
 
0.1%
0.76 7
 
0.1%
0.78 7
 
0.1%
0.79 3
 
< 0.1%
0.8 24
 
0.3%
ValueCountFrequency (%)
164.73 1
 
< 0.1%
154.12 1
 
< 0.1%
147.12 2
 
< 0.1%
143.71 1
 
< 0.1%
130 1
 
< 0.1%
126 1
 
< 0.1%
110.2 10
0.1%
99 7
0.1%
91.05 5
 
0.1%
89.3 13
0.2%
Distinct795
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
2024-07-09T17:21:57.022838image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length22
Median length19
Mean length12.867127
Min length7

Characters and Unicode

Total characters108071
Distinct characters53
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)0.1%

Sample

1st rowMuhammed MacIntyre
2nd rowBarry French
3rd rowBarry French
4th rowClay Rozendal
5th rowCarlos Soltero
ValueCountFrequency (%)
michael 105
 
0.6%
john 93
 
0.6%
brown 93
 
0.6%
liz 87
 
0.5%
michelle 86
 
0.5%
jones 86
 
0.5%
patrick 83
 
0.5%
bill 80
 
0.5%
alan 77
 
0.5%
price 75
 
0.4%
Other values (895) 15961
94.9%
2024-07-09T17:21:58.034911image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 10075
 
9.3%
e 9451
 
8.7%
n 8461
 
7.8%
8427
 
7.8%
r 7919
 
7.3%
i 6569
 
6.1%
l 5720
 
5.3%
o 5302
 
4.9%
t 4465
 
4.1%
s 3528
 
3.3%
Other values (43) 38154
35.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 82315
76.2%
Uppercase Letter 17202
 
15.9%
Space Separator 8427
 
7.8%
Other Punctuation 127
 
0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
C 1563
 
9.1%
B 1510
 
8.8%
M 1487
 
8.6%
S 1487
 
8.6%
D 1121
 
6.5%
J 1009
 
5.9%
A 988
 
5.7%
P 880
 
5.1%
H 796
 
4.6%
T 784
 
4.6%
Other values (16) 5577
32.4%
Lowercase Letter
ValueCountFrequency (%)
a 10075
12.2%
e 9451
11.5%
n 8461
10.3%
r 7919
9.6%
i 6569
 
8.0%
l 5720
 
6.9%
o 5302
 
6.4%
t 4465
 
5.4%
s 3528
 
4.3%
h 3269
 
4.0%
Other values (15) 17556
21.3%
Space Separator
ValueCountFrequency (%)
8427
100.0%
Other Punctuation
ValueCountFrequency (%)
' 127
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 99517
92.1%
Common 8554
 
7.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 10075
 
10.1%
e 9451
 
9.5%
n 8461
 
8.5%
r 7919
 
8.0%
i 6569
 
6.6%
l 5720
 
5.7%
o 5302
 
5.3%
t 4465
 
4.5%
s 3528
 
3.5%
h 3269
 
3.3%
Other values (41) 34758
34.9%
Common
ValueCountFrequency (%)
8427
98.5%
' 127
 
1.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 108071
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 10075
 
9.3%
e 9451
 
8.7%
n 8461
 
7.8%
8427
 
7.8%
r 7919
 
7.3%
i 6569
 
6.1%
l 5720
 
5.3%
o 5302
 
4.9%
t 4465
 
4.1%
s 3528
 
3.3%
Other values (43) 38154
35.3%

Province
Categorical

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Ontario
1826 
British Columbia
1126 
Saskachewan
913 
Alberta
865 
Manitoba
793 
Other values (8)
2876 

Length

Max length21
Median length16
Mean length9.9976188
Min length5

Characters and Unicode

Total characters83970
Distinct characters33
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNunavut
2nd rowNunavut
3rd rowNunavut
4th rowNunavut
5th rowNunavut

Common Values

ValueCountFrequency (%)
Ontario 1826
21.7%
British Columbia 1126
13.4%
Saskachewan 913
10.9%
Alberta 865
10.3%
Manitoba 793
9.4%
Quebec 781
9.3%
Yukon 542
 
6.5%
Nova Scotia 464
 
5.5%
Northwest Territories 394
 
4.7%
New Brunswick 323
 
3.8%
Other values (3) 372
 
4.4%

Length

2024-07-09T17:21:58.329126image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
ontario 1826
16.4%
british 1126
10.1%
columbia 1126
10.1%
saskachewan 913
8.2%
alberta 865
 
7.8%
manitoba 793
 
7.1%
quebec 781
 
7.0%
yukon 542
 
4.9%
scotia 464
 
4.2%
nova 464
 
4.2%
Other values (9) 2228
20.0%

Most occurring characters

ValueCountFrequency (%)
a 9653
 
11.5%
i 7783
 
9.3%
t 6335
 
7.5%
r 6138
 
7.3%
o 6085
 
7.2%
e 5138
 
6.1%
n 5062
 
6.0%
b 3565
 
4.2%
s 3361
 
4.0%
u 3012
 
3.6%
Other values (23) 27838
33.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70113
83.5%
Uppercase Letter 11128
 
13.3%
Space Separator 2729
 
3.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 9653
13.8%
i 7783
11.1%
t 6335
9.0%
r 6138
8.8%
o 6085
8.7%
e 5138
 
7.3%
n 5062
 
7.2%
b 3565
 
5.1%
s 3361
 
4.8%
u 3012
 
4.3%
Other values (9) 13981
19.9%
Uppercase Letter
ValueCountFrequency (%)
O 1826
16.4%
B 1449
13.0%
S 1377
12.4%
N 1342
12.1%
C 1126
10.1%
A 865
7.8%
M 793
7.1%
Q 781
7.0%
Y 542
 
4.9%
T 394
 
3.5%
Other values (3) 633
 
5.7%
Space Separator
ValueCountFrequency (%)
2729
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 81241
96.8%
Common 2729
 
3.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 9653
 
11.9%
i 7783
 
9.6%
t 6335
 
7.8%
r 6138
 
7.6%
o 6085
 
7.5%
e 5138
 
6.3%
n 5062
 
6.2%
b 3565
 
4.4%
s 3361
 
4.1%
u 3012
 
3.7%
Other values (22) 25109
30.9%
Common
ValueCountFrequency (%)
2729
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83970
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 9653
 
11.5%
i 7783
 
9.3%
t 6335
 
7.5%
r 6138
 
7.3%
o 6085
 
7.2%
e 5138
 
6.1%
n 5062
 
6.0%
b 3565
 
4.2%
s 3361
 
4.0%
u 3012
 
3.6%
Other values (23) 27838
33.2%

Region
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
West
1991 
Ontario
1826 
Prarie
1706 
Atlantic
1080 
Quebec
781 
Other values (3)
1015 

Length

Max length21
Median length8
Mean length6.6490058
Min length4

Characters and Unicode

Total characters55845
Distinct characters25
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNunavut
2nd rowNunavut
3rd rowNunavut
4th rowNunavut
5th rowNunavut

Common Values

ValueCountFrequency (%)
West 1991
23.7%
Ontario 1826
21.7%
Prarie 1706
20.3%
Atlantic 1080
12.9%
Quebec 781
 
9.3%
Yukon 542
 
6.5%
Northwest Territories 394
 
4.7%
Nunavut 79
 
0.9%

Length

2024-07-09T17:21:58.615247image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:21:58.869182image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
west 1991
22.6%
ontario 1826
20.8%
prarie 1706
19.4%
atlantic 1080
12.3%
quebec 781
 
8.9%
yukon 542
 
6.2%
northwest 394
 
4.5%
territories 394
 
4.5%
nunavut 79
 
0.9%

Most occurring characters

ValueCountFrequency (%)
t 7238
13.0%
r 6814
12.2%
e 6441
11.5%
i 5400
9.7%
a 4691
 
8.4%
n 3527
 
6.3%
o 3156
 
5.7%
s 2779
 
5.0%
W 1991
 
3.6%
c 1861
 
3.3%
Other values (15) 11947
21.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 46658
83.5%
Uppercase Letter 8793
 
15.7%
Space Separator 394
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 7238
15.5%
r 6814
14.6%
e 6441
13.8%
i 5400
11.6%
a 4691
10.1%
n 3527
7.6%
o 3156
6.8%
s 2779
 
6.0%
c 1861
 
4.0%
u 1481
 
3.2%
Other values (6) 3270
7.0%
Uppercase Letter
ValueCountFrequency (%)
W 1991
22.6%
O 1826
20.8%
P 1706
19.4%
A 1080
12.3%
Q 781
 
8.9%
Y 542
 
6.2%
N 473
 
5.4%
T 394
 
4.5%
Space Separator
ValueCountFrequency (%)
394
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 55451
99.3%
Common 394
 
0.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 7238
13.1%
r 6814
12.3%
e 6441
11.6%
i 5400
9.7%
a 4691
8.5%
n 3527
 
6.4%
o 3156
 
5.7%
s 2779
 
5.0%
W 1991
 
3.6%
c 1861
 
3.4%
Other values (14) 11553
20.8%
Common
ValueCountFrequency (%)
394
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55845
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
t 7238
13.0%
r 6814
12.2%
e 6441
11.5%
i 5400
9.7%
a 4691
 
8.4%
n 3527
 
6.3%
o 3156
 
5.7%
s 2779
 
5.0%
W 1991
 
3.6%
c 1861
 
3.3%
Other values (15) 11947
21.4%

Customer Segment
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Corporate
3076 
Home Office
2032 
Consumer
1649 
Small Business
1642 

Length

Max length14
Median length11
Mean length10.265032
Min length8

Characters and Unicode

Total characters86216
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSmall Business
2nd rowConsumer
3rd rowConsumer
4th rowCorporate
5th rowConsumer

Common Values

ValueCountFrequency (%)
Corporate 3076
36.6%
Home Office 2032
24.2%
Consumer 1649
19.6%
Small Business 1642
19.5%

Length

2024-07-09T17:21:59.170358image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:21:59.398416image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
corporate 3076
25.5%
home 2032
16.8%
office 2032
16.8%
consumer 1649
13.7%
small 1642
13.6%
business 1642
13.6%

Most occurring characters

ValueCountFrequency (%)
e 10431
12.1%
o 9833
 
11.4%
r 7801
 
9.0%
s 6575
 
7.6%
m 5323
 
6.2%
C 4725
 
5.5%
a 4718
 
5.5%
f 4064
 
4.7%
3674
 
4.3%
i 3674
 
4.3%
Other values (10) 25398
29.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 70469
81.7%
Uppercase Letter 12073
 
14.0%
Space Separator 3674
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 10431
14.8%
o 9833
14.0%
r 7801
11.1%
s 6575
9.3%
m 5323
7.6%
a 4718
6.7%
f 4064
 
5.8%
i 3674
 
5.2%
u 3291
 
4.7%
n 3291
 
4.7%
Other values (4) 11468
16.3%
Uppercase Letter
ValueCountFrequency (%)
C 4725
39.1%
O 2032
16.8%
H 2032
16.8%
S 1642
 
13.6%
B 1642
 
13.6%
Space Separator
ValueCountFrequency (%)
3674
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 82542
95.7%
Common 3674
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 10431
12.6%
o 9833
11.9%
r 7801
 
9.5%
s 6575
 
8.0%
m 5323
 
6.4%
C 4725
 
5.7%
a 4718
 
5.7%
f 4064
 
4.9%
i 3674
 
4.5%
u 3291
 
4.0%
Other values (9) 22107
26.8%
Common
ValueCountFrequency (%)
3674
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 86216
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 10431
12.1%
o 9833
 
11.4%
r 7801
 
9.0%
s 6575
 
7.6%
m 5323
 
6.2%
C 4725
 
5.5%
a 4718
 
5.5%
f 4064
 
4.7%
3674
 
4.3%
i 3674
 
4.3%
Other values (10) 25398
29.5%

Product Category
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Office Supplies
4610 
Technology
2065 
Furniture
1724 

Length

Max length15
Median length15
Mean length12.539112
Min length9

Characters and Unicode

Total characters105316
Distinct characters20
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOffice Supplies
2nd rowOffice Supplies
3rd rowOffice Supplies
4th rowTechnology
5th rowOffice Supplies

Common Values

ValueCountFrequency (%)
Office Supplies 4610
54.9%
Technology 2065
24.6%
Furniture 1724
 
20.5%

Length

2024-07-09T17:21:59.676426image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:21:59.904639image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
office 4610
35.4%
supplies 4610
35.4%
technology 2065
15.9%
furniture 1724
 
13.3%

Most occurring characters

ValueCountFrequency (%)
e 13009
12.4%
i 10944
 
10.4%
p 9220
 
8.8%
f 9220
 
8.8%
u 8058
 
7.7%
c 6675
 
6.3%
l 6675
 
6.3%
O 4610
 
4.4%
s 4610
 
4.4%
S 4610
 
4.4%
Other values (10) 27685
26.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 87697
83.3%
Uppercase Letter 13009
 
12.4%
Space Separator 4610
 
4.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 13009
14.8%
i 10944
12.5%
p 9220
10.5%
f 9220
10.5%
u 8058
9.2%
c 6675
7.6%
l 6675
7.6%
s 4610
 
5.3%
o 4130
 
4.7%
n 3789
 
4.3%
Other values (5) 11367
13.0%
Uppercase Letter
ValueCountFrequency (%)
O 4610
35.4%
S 4610
35.4%
T 2065
15.9%
F 1724
 
13.3%
Space Separator
ValueCountFrequency (%)
4610
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 100706
95.6%
Common 4610
 
4.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 13009
12.9%
i 10944
10.9%
p 9220
 
9.2%
f 9220
 
9.2%
u 8058
 
8.0%
c 6675
 
6.6%
l 6675
 
6.6%
O 4610
 
4.6%
s 4610
 
4.6%
S 4610
 
4.6%
Other values (9) 23075
22.9%
Common
ValueCountFrequency (%)
4610
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 105316
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 13009
12.4%
i 10944
 
10.4%
p 9220
 
8.8%
f 9220
 
8.8%
u 8058
 
7.7%
c 6675
 
6.3%
l 6675
 
6.3%
O 4610
 
4.4%
s 4610
 
4.4%
S 4610
 
4.4%
Other values (10) 27685
26.3%
Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Paper
1225 
Binders and Binder Accessories
915 
Telephones and Communication
883 
Office Furnishings
788 
Computer Peripherals
758 
Other values (12)
3830 

Length

Max length30
Median length20
Mean length17.080962
Min length5

Characters and Unicode

Total characters143463
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowStorage & Organization
2nd rowAppliances
3rd rowBinders and Binder Accessories
4th rowTelephones and Communication
5th rowAppliances

Common Values

ValueCountFrequency (%)
Paper 1225
14.6%
Binders and Binder Accessories 915
10.9%
Telephones and Communication 883
10.5%
Office Furnishings 788
9.4%
Computer Peripherals 758
9.0%
Pens & Art Supplies 633
7.5%
Storage & Organization 546
 
6.5%
Appliances 434
 
5.2%
Chairs & Chairmats 386
 
4.6%
Tables 361
 
4.3%
Other values (7) 1470
17.5%

Length

2024-07-09T17:22:00.198159image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
and 2029
 
10.5%
1565
 
8.1%
paper 1225
 
6.3%
office 1125
 
5.8%
binders 915
 
4.7%
binder 915
 
4.7%
accessories 915
 
4.7%
telephones 883
 
4.6%
communication 883
 
4.6%
furnishings 788
 
4.1%
Other values (22) 8098
41.9%

Most occurring characters

ValueCountFrequency (%)
e 15400
 
10.7%
s 11945
 
8.3%
i 11613
 
8.1%
n 11005
 
7.7%
10942
 
7.6%
r 10371
 
7.2%
a 9566
 
6.7%
o 6269
 
4.4%
p 6091
 
4.2%
c 4942
 
3.4%
Other values (27) 45319
31.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 115065
80.2%
Uppercase Letter 15747
 
11.0%
Space Separator 10942
 
7.6%
Other Punctuation 1709
 
1.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 15400
13.4%
s 11945
10.4%
i 11613
10.1%
n 11005
9.6%
r 10371
9.0%
a 9566
8.3%
o 6269
 
5.4%
p 6091
 
5.3%
c 4942
 
4.3%
d 4038
 
3.5%
Other values (12) 23825
20.7%
Uppercase Letter
ValueCountFrequency (%)
P 2616
16.6%
C 2500
15.9%
B 2198
14.0%
A 1982
12.6%
O 1671
10.6%
T 1388
8.8%
S 1323
8.4%
F 875
 
5.6%
M 337
 
2.1%
R 323
 
2.1%
Other values (2) 534
 
3.4%
Other Punctuation
ValueCountFrequency (%)
& 1565
91.6%
, 144
 
8.4%
Space Separator
ValueCountFrequency (%)
10942
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 130812
91.2%
Common 12651
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 15400
 
11.8%
s 11945
 
9.1%
i 11613
 
8.9%
n 11005
 
8.4%
r 10371
 
7.9%
a 9566
 
7.3%
o 6269
 
4.8%
p 6091
 
4.7%
c 4942
 
3.8%
d 4038
 
3.1%
Other values (24) 39572
30.3%
Common
ValueCountFrequency (%)
10942
86.5%
& 1565
 
12.4%
, 144
 
1.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 143463
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 15400
 
10.7%
s 11945
 
8.3%
i 11613
 
8.1%
n 11005
 
7.7%
10942
 
7.6%
r 10371
 
7.2%
a 9566
 
6.7%
o 6269
 
4.4%
p 6091
 
4.2%
c 4942
 
3.4%
Other values (27) 45319
31.6%
Distinct1263
Distinct (%)15.0%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
2024-07-09T17:22:00.804080image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Length

Max length98
Median length75
Mean length34.351709
Min length3

Characters and Unicode

Total characters288520
Distinct characters84
Distinct categories12 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)0.7%

Sample

1st rowEldon Base for stackable storage shelf, platinum
2nd row1.7 Cubic Foot Compact "Cube" Office Refrigerators
3rd rowCardinal Slant-D® Ring Binder, Heavy Gauge Vinyl
4th rowR380
5th rowHolmes HEPA Air Purifier
ValueCountFrequency (%)
xerox 765
 
1.8%
x 499
 
1.2%
avery 418
 
1.0%
with 405
 
0.9%
black 338
 
0.8%
327
 
0.8%
binders 305
 
0.7%
for 302
 
0.7%
chair 276
 
0.6%
keyboard 268
 
0.6%
Other values (2076) 38861
90.9%
2024-07-09T17:22:01.755186image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
34365
 
11.9%
e 25862
 
9.0%
r 15875
 
5.5%
o 15517
 
5.4%
a 14627
 
5.1%
i 14001
 
4.9%
l 12489
 
4.3%
t 12482
 
4.3%
n 11792
 
4.1%
s 11438
 
4.0%
Other values (74) 120072
41.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 184442
63.9%
Uppercase Letter 42833
 
14.8%
Space Separator 34365
 
11.9%
Decimal Number 16531
 
5.7%
Other Punctuation 6372
 
2.2%
Dash Punctuation 2329
 
0.8%
Other Symbol 1374
 
0.5%
Final Punctuation 69
 
< 0.1%
Close Punctuation 68
 
< 0.1%
Open Punctuation 68
 
< 0.1%
Other values (2) 69
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 25862
14.0%
r 15875
 
8.6%
o 15517
 
8.4%
a 14627
 
7.9%
i 14001
 
7.6%
l 12489
 
6.8%
t 12482
 
6.8%
n 11792
 
6.4%
s 11438
 
6.2%
c 7441
 
4.0%
Other values (17) 42918
23.3%
Uppercase Letter
ValueCountFrequency (%)
S 4518
 
10.5%
C 4434
 
10.4%
P 4013
 
9.4%
B 3859
 
9.0%
D 2625
 
6.1%
A 2478
 
5.8%
M 2403
 
5.6%
F 2020
 
4.7%
T 1985
 
4.6%
R 1664
 
3.9%
Other values (16) 12834
30.0%
Decimal Number
ValueCountFrequency (%)
1 3209
19.4%
0 2724
16.5%
2 1984
12.0%
3 1528
9.2%
8 1410
8.5%
4 1406
8.5%
9 1255
 
7.6%
5 1142
 
6.9%
6 943
 
5.7%
7 930
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 2856
44.8%
/ 1359
21.3%
" 1060
 
16.6%
. 520
 
8.2%
& 216
 
3.4%
' 149
 
2.3%
# 104
 
1.6%
* 59
 
0.9%
% 45
 
0.7%
; 4
 
0.1%
Other Symbol
ValueCountFrequency (%)
® 896
65.2%
478
34.8%
Close Punctuation
ValueCountFrequency (%)
) 53
77.9%
] 15
 
22.1%
Open Punctuation
ValueCountFrequency (%)
( 53
77.9%
[ 15
 
22.1%
Space Separator
ValueCountFrequency (%)
34365
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2329
100.0%
Final Punctuation
ValueCountFrequency (%)
69
100.0%
Math Symbol
ValueCountFrequency (%)
+ 40
100.0%
Initial Punctuation
ValueCountFrequency (%)
29
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 227275
78.8%
Common 61245
 
21.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 25862
 
11.4%
r 15875
 
7.0%
o 15517
 
6.8%
a 14627
 
6.4%
i 14001
 
6.2%
l 12489
 
5.5%
t 12482
 
5.5%
n 11792
 
5.2%
s 11438
 
5.0%
c 7441
 
3.3%
Other values (43) 85751
37.7%
Common
ValueCountFrequency (%)
34365
56.1%
1 3209
 
5.2%
, 2856
 
4.7%
0 2724
 
4.4%
- 2329
 
3.8%
2 1984
 
3.2%
3 1528
 
2.5%
8 1410
 
2.3%
4 1406
 
2.3%
/ 1359
 
2.2%
Other values (21) 8075
 
13.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 287046
99.5%
None 898
 
0.3%
Letterlike Symbols 478
 
0.2%
Punctuation 98
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
34365
 
12.0%
e 25862
 
9.0%
r 15875
 
5.5%
o 15517
 
5.4%
a 14627
 
5.1%
i 14001
 
4.9%
l 12489
 
4.4%
t 12482
 
4.3%
n 11792
 
4.1%
s 11438
 
4.0%
Other values (69) 118598
41.3%
None
ValueCountFrequency (%)
® 896
99.8%
à 2
 
0.2%
Letterlike Symbols
ValueCountFrequency (%)
478
100.0%
Punctuation
ValueCountFrequency (%)
69
70.4%
29
29.6%
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Small Box
4347 
Wrap Bag
1168 
Small Pack
956 
Jumbo Drum
624 
Jumbo Box
532 
Other values (2)
772 

Length

Max length10
Median length9
Mean length9.0926301
Min length8

Characters and Unicode

Total characters76369
Distinct characters24
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLarge Box
2nd rowJumbo Drum
3rd rowSmall Box
4th rowSmall Box
5th rowMedium Box

Common Values

ValueCountFrequency (%)
Small Box 4347
51.8%
Wrap Bag 1168
 
13.9%
Small Pack 956
 
11.4%
Jumbo Drum 624
 
7.4%
Jumbo Box 532
 
6.3%
Large Box 406
 
4.8%
Medium Box 366
 
4.4%

Length

2024-07-09T17:22:02.040931image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:22:02.309398image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
box 5651
33.6%
small 5303
31.6%
wrap 1168
 
7.0%
bag 1168
 
7.0%
jumbo 1156
 
6.9%
pack 956
 
5.7%
drum 624
 
3.7%
large 406
 
2.4%
medium 366
 
2.2%

Most occurring characters

ValueCountFrequency (%)
l 10606
13.9%
a 9001
11.8%
8399
11.0%
m 7449
9.8%
B 6819
8.9%
o 6807
8.9%
x 5651
7.4%
S 5303
6.9%
r 2198
 
2.9%
u 2146
 
2.8%
Other values (14) 11990
15.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 51172
67.0%
Uppercase Letter 16798
 
22.0%
Space Separator 8399
 
11.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 10606
20.7%
a 9001
17.6%
m 7449
14.6%
o 6807
13.3%
x 5651
11.0%
r 2198
 
4.3%
u 2146
 
4.2%
g 1574
 
3.1%
p 1168
 
2.3%
b 1156
 
2.3%
Other values (5) 3416
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
B 6819
40.6%
S 5303
31.6%
W 1168
 
7.0%
J 1156
 
6.9%
P 956
 
5.7%
D 624
 
3.7%
L 406
 
2.4%
M 366
 
2.2%
Space Separator
ValueCountFrequency (%)
8399
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 67970
89.0%
Common 8399
 
11.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 10606
15.6%
a 9001
13.2%
m 7449
11.0%
B 6819
10.0%
o 6807
10.0%
x 5651
8.3%
S 5303
7.8%
r 2198
 
3.2%
u 2146
 
3.2%
g 1574
 
2.3%
Other values (13) 10416
15.3%
Common
ValueCountFrequency (%)
8399
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 76369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 10606
13.9%
a 9001
11.8%
8399
11.0%
m 7449
9.8%
B 6819
8.9%
o 6807
8.9%
x 5651
7.4%
S 5303
6.9%
r 2198
 
2.9%
u 2146
 
2.8%
Other values (14) 11990
15.7%

Product Base Margin
Real number (ℝ)

Distinct51
Distinct (%)0.6%
Missing63
Missing (%)0.8%
Infinite0
Infinite (%)0.0%
Mean0.5125132
Minimum0.35
Maximum0.85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size65.7 KiB
2024-07-09T17:22:02.611507image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Quantile statistics

Minimum0.35
5-th percentile0.36
Q10.38
median0.52
Q30.59
95-th percentile0.78
Maximum0.85
Range0.5
Interquartile range (IQR)0.21

Descriptive statistics

Standard deviation0.13558894
Coefficient of variation (CV)0.26455698
Kurtosis-0.66087023
Mean0.5125132
Median Absolute Deviation (MAD)0.12
Skewness0.55939959
Sum4272.31
Variance0.018384361
MonotonicityNot monotonic
2024-07-09T17:22:02.913624image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.37 761
 
9.1%
0.38 678
 
8.1%
0.36 628
 
7.5%
0.59 497
 
5.9%
0.39 482
 
5.7%
0.57 459
 
5.5%
0.56 459
 
5.5%
0.4 408
 
4.9%
0.58 387
 
4.6%
0.55 314
 
3.7%
Other values (41) 3263
38.8%
ValueCountFrequency (%)
0.35 262
 
3.1%
0.36 628
7.5%
0.37 761
9.1%
0.38 678
8.1%
0.39 482
5.7%
0.4 408
4.9%
0.41 98
 
1.2%
0.42 78
 
0.9%
0.43 101
 
1.2%
0.44 94
 
1.1%
ValueCountFrequency (%)
0.85 36
0.4%
0.84 25
 
0.3%
0.83 83
1.0%
0.82 32
 
0.4%
0.81 73
0.9%
0.8 48
0.6%
0.79 68
0.8%
0.78 89
1.1%
0.77 68
0.8%
0.76 55
0.7%
Distinct1450
Distinct (%)17.3%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
Minimum2009-01-02 00:00:00
Maximum2012-12-30 00:00:00
2024-07-09T17:22:03.206840image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:22:03.525751image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Year
Categorical

Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size65.7 KiB
2009
2153 
2010
2142 
2012
2102 
2011
2002 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters33596
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2010
2nd row2012
3rd row2012
4th row2011
5th row2010

Common Values

ValueCountFrequency (%)
2009 2153
25.6%
2010 2142
25.5%
2012 2102
25.0%
2011 2002
23.8%

Length

2024-07-09T17:22:03.812379image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-07-09T17:22:04.040668image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
ValueCountFrequency (%)
2009 2153
25.6%
2010 2142
25.5%
2012 2102
25.0%
2011 2002
23.8%

Most occurring characters

ValueCountFrequency (%)
0 12694
37.8%
2 10501
31.3%
1 8248
24.6%
9 2153
 
6.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 33596
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 12694
37.8%
2 10501
31.3%
1 8248
24.6%
9 2153
 
6.4%

Most occurring scripts

ValueCountFrequency (%)
Common 33596
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 12694
37.8%
2 10501
31.3%
1 8248
24.6%
9 2153
 
6.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 33596
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 12694
37.8%
2 10501
31.3%
1 8248
24.6%
9 2153
 
6.4%

Interactions

2024-07-09T17:21:46.697232image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:32.511380image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:34.237035image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:36.045345image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:37.820246image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:39.508814image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:41.262198image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:42.926795image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:44.761821image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:46.882924image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:32.731337image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:34.416567image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:36.225163image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:37.991547image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:39.696498image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:41.433697image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:43.139123image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:44.941184image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:47.092087image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:32.926929image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:34.629459image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:36.430142image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:38.186943image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:39.908409image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:41.645966image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:43.352647image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:45.160665image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:47.317361image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:33.114097image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:34.826100image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:36.610736image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:38.374640image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:40.103542image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:41.833055image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:43.548286image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:45.363819image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:47.504016image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:33.297606image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:35.013571image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:36.823141image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:38.537617image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:40.282730image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:42.021111image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:43.737010image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:45.621241image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:47.691977image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:33.477350image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:35.217663image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:37.019015image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:38.733833image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:40.486860image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:42.200372image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:43.948644image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:45.834239image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:47.871521image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:33.657500image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:35.417189image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:37.198418image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:38.921506image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:40.658437image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:42.363466image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:44.152443image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:46.028266image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:48.075426image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:33.861140image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:35.637492image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:37.419248image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:39.116760image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:40.878997image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:42.559086image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:44.369640image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:46.270466image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:48.279068image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:34.049076image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:35.849484image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:37.616417image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:39.320912image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:41.074919image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:42.746759image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:44.573820image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
2024-07-09T17:21:46.466183image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/

Missing values

2024-07-09T17:21:49.120723image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
A simple visualization of nullity by column.
2024-07-09T17:21:49.798949image/svg+xmlMatplotlib v3.8.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

Row IDOrder IDOrder DateOrder PriorityOrder QuantitySalesDiscountShip ModeProfitUnit PriceShipping CostCustomer NameProvinceRegionCustomer SegmentProduct CategoryProduct Sub-CategoryProduct NameProduct ContainerProduct Base MarginShip DateYear
0132010-10-13Low6261.54000.04Regular Air-213.250038.9435.00Muhammed MacIntyreNunavutNunavutSmall BusinessOffice SuppliesStorage & OrganizationEldon Base for stackable storage shelf, platinumLarge Box0.802010-10-202010
1492932012-10-01High4910123.02000.07Delivery Truck457.8100208.1668.02Barry FrenchNunavutNunavutConsumerOffice SuppliesAppliances1.7 Cubic Foot Compact "Cube" Office RefrigeratorsJumbo Drum0.582012-10-022012
2502932012-10-01High27244.57000.01Regular Air46.70758.692.99Barry FrenchNunavutNunavutConsumerOffice SuppliesBinders and Binder AccessoriesCardinal Slant-D® Ring Binder, Heavy Gauge VinylSmall Box0.392012-10-032012
3804832011-07-10High304965.75950.08Regular Air1198.9710195.993.99Clay RozendalNunavutNunavutCorporateTechnologyTelephones and CommunicationR380Small Box0.582011-07-122011
4855152010-08-28Not Specified19394.27000.08Regular Air30.940021.785.94Carlos SolteroNunavutNunavutConsumerOffice SuppliesAppliancesHolmes HEPA Air PurifierMedium Box0.502010-08-302010
5865152010-08-28Not Specified21146.69000.05Regular Air4.43006.644.95Carlos SolteroNunavutNunavutConsumerFurnitureOffice FurnishingsG.E. Longer-Life Indoor Recessed Floodlight BulbsSmall Pack0.372010-08-302010
6976132011-06-17High1293.54000.03Regular Air-54.03857.307.72Carl JacksonNunavutNunavutCorporateOffice SuppliesBinders and Binder AccessoriesAngle-D Binders with Locking Rings, Label HoldersSmall Box0.382011-06-172011
7986132011-06-17High22905.08000.09Regular Air127.700042.766.22Carl JacksonNunavutNunavutCorporateOffice SuppliesStorage & OrganizationSAFCO Mobile Desk Side File, Wire FrameSmall BoxNaN2011-06-182011
81036432011-03-24High212781.82000.07Express Air-695.2600138.1435.00Monica FederleNunavutNunavutCorporateOffice SuppliesStorage & OrganizationSAFCO Commercial Wire Shelving, BlackLarge BoxNaN2011-03-252011
91076782010-02-26Low44228.41000.07Regular Air-226.36004.988.33Dorothy BaddersNunavutNunavutHome OfficeOffice SuppliesPaperXerox 198Small Box0.382010-02-262010
Row IDOrder IDOrder DateOrder PriorityOrder QuantitySalesDiscountShip ModeProfitUnit PriceShipping CostCustomer NameProvinceRegionCustomer SegmentProduct CategoryProduct Sub-CategoryProduct NameProduct ContainerProduct Base MarginShip DateYear
83896492462122012-09-12Not Specified43322.47000.09Express Air72.28007.782.50Grant DonatelliAlbertaWestConsumerOffice SuppliesEnvelopesStaples #10 Colored EnvelopesSmall Box0.382012-09-142012
83906526464372009-09-15Medium491488.66000.00Regular Air385.370029.347.87Mick BrownAlbertaWestConsumerFurnitureOffice FurnishingsSeth Thomas 14" Putty-Colored Wall ClockSmall Box0.542009-09-172009
83916657473602010-10-08Not Specified252200.64000.05Delivery Truck-514.180089.9942.00Frank HawleyAlbertaWestHome OfficeFurnitureChairs & ChairmatsGlobal Leather Task Chair, BlackJumbo Drum0.662010-10-102010
83927396527062012-07-09Low341041.66000.02Express Air480.530528.531.49Harry GreeneAlbertaWestCorporateOffice SuppliesBinders and Binder AccessoriesLock-Up Easel 'Spel-Binder'Small Box0.382012-07-162012
83937586542792011-07-30High4110071.09000.10Delivery Truck1977.6900264.9817.86Harry GreeneAlbertaWestCorporateTechnologyOffice MachinesPanasonic KX-P1131 Dot Matrix PrinterJumbo Drum0.582011-07-312011
83947765555582010-08-09Medium81294.04000.05Delivery Truck-323.1800150.9866.27Mick BrownAlbertaWestConsumerFurnitureBookcasesBush Mission Pointe LibraryJumbo Box0.652010-08-092010
83957766555582010-08-09Medium23392.57000.04Regular Air22.250017.078.13Mick BrownAlbertaWestConsumerOffice SuppliesEnvelopesRecycled Interoffice Envelopes with Re-Use-A-Seal® Closure, 10 x 13Small Box0.382010-08-112010
83967906565502011-04-08Not Specified37823.78000.03Express Air343.050022.235.08Frank HawleyAlbertaWestHome OfficeFurnitureOffice FurnishingsExecutive Impressions 14"Small Pack0.412011-04-102011
83977907565502011-04-08Not Specified8469.83750.00Regular Air-159.236065.998.99Frank HawleyAlbertaWestHome OfficeTechnologyTelephones and CommunicationTalkabout T8367Small Box0.562011-04-092011
83987914565812009-02-08High202026.01000.10Express Air580.4300105.9813.99Grant DonatelliAlbertaWestConsumerFurnitureOffice FurnishingsTenex 46" x 60" Computer Anti-Static Chairmat, Rectangular ShapedMedium Box0.652009-02-112009